{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# PyCaret Stock Prediction"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      },
      "id": "53f45e90-b569-41af-af6e-4264d4625024"
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# yahoo finance used to fetch data \n",
        "import yfinance as yf\n",
        "yf.pdr_override()"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {},
      "id": "a8e60537"
    },
    {
      "cell_type": "code",
      "source": [
        "df= yf.download(\"AMD\", start=\"2020-01-01\", end=\"2022-01-01\")"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n"
          ]
        }
      ],
      "execution_count": 2,
      "metadata": {},
      "id": "276d2697"
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Adj Close</th>\n      <th>Volume</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2020-01-02</th>\n      <td>46.860001</td>\n      <td>49.250000</td>\n      <td>46.630001</td>\n      <td>49.099998</td>\n      <td>49.099998</td>\n      <td>80331100</td>\n    </tr>\n    <tr>\n      <th>2020-01-03</th>\n      <td>48.029999</td>\n      <td>49.389999</td>\n      <td>47.540001</td>\n      <td>48.599998</td>\n      <td>48.599998</td>\n      <td>73127400</td>\n    </tr>\n    <tr>\n      <th>2020-01-06</th>\n      <td>48.020000</td>\n      <td>48.860001</td>\n      <td>47.860001</td>\n      <td>48.389999</td>\n      <td>48.389999</td>\n      <td>47934900</td>\n    </tr>\n    <tr>\n      <th>2020-01-07</th>\n      <td>49.349998</td>\n      <td>49.389999</td>\n      <td>48.040001</td>\n      <td>48.250000</td>\n      <td>48.250000</td>\n      <td>58061400</td>\n    </tr>\n    <tr>\n      <th>2020-01-08</th>\n      <td>47.849998</td>\n      <td>48.299999</td>\n      <td>47.139999</td>\n      <td>47.830002</td>\n      <td>47.830002</td>\n      <td>53767000</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "                 Open       High        Low      Close  Adj Close    Volume\nDate                                                                       \n2020-01-02  46.860001  49.250000  46.630001  49.099998  49.099998  80331100\n2020-01-03  48.029999  49.389999  47.540001  48.599998  48.599998  73127400\n2020-01-06  48.020000  48.860001  47.860001  48.389999  48.389999  47934900\n2020-01-07  49.349998  49.389999  48.040001  48.250000  48.250000  58061400\n2020-01-08  47.849998  48.299999  47.139999  47.830002  47.830002  53767000"
          },
          "metadata": {}
        }
      ],
      "execution_count": 3,
      "metadata": {},
      "id": "54686652"
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Adj Close</th>\n      <th>Volume</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-12-27</th>\n      <td>147.509995</td>\n      <td>154.889999</td>\n      <td>147.250000</td>\n      <td>154.360001</td>\n      <td>154.360001</td>\n      <td>53296400</td>\n    </tr>\n    <tr>\n      <th>2021-12-28</th>\n      <td>155.880005</td>\n      <td>156.729996</td>\n      <td>151.380005</td>\n      <td>153.149994</td>\n      <td>153.149994</td>\n      <td>58699100</td>\n    </tr>\n    <tr>\n      <th>2021-12-29</th>\n      <td>152.820007</td>\n      <td>154.339996</td>\n      <td>147.289993</td>\n      <td>148.259995</td>\n      <td>148.259995</td>\n      <td>51300200</td>\n    </tr>\n    <tr>\n      <th>2021-12-30</th>\n      <td>147.440002</td>\n      <td>148.850006</td>\n      <td>144.850006</td>\n      <td>145.149994</td>\n      <td>145.149994</td>\n      <td>44358000</td>\n    </tr>\n    <tr>\n      <th>2021-12-31</th>\n      <td>146.160004</td>\n      <td>148.610001</td>\n      <td>143.550003</td>\n      <td>143.899994</td>\n      <td>143.899994</td>\n      <td>49448100</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "                  Open        High         Low       Close   Adj Close  \\\nDate                                                                     \n2021-12-27  147.509995  154.889999  147.250000  154.360001  154.360001   \n2021-12-28  155.880005  156.729996  151.380005  153.149994  153.149994   \n2021-12-29  152.820007  154.339996  147.289993  148.259995  148.259995   \n2021-12-30  147.440002  148.850006  144.850006  145.149994  145.149994   \n2021-12-31  146.160004  148.610001  143.550003  143.899994  143.899994   \n\n              Volume  \nDate                  \n2021-12-27  53296400  \n2021-12-28  58699100  \n2021-12-29  51300200  \n2021-12-30  44358000  \n2021-12-31  49448100  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 4,
      "metadata": {},
      "id": "edc23451"
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "(505, 6)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 5,
      "metadata": {},
      "id": "28b38739"
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.reset_index()"
      ],
      "outputs": [],
      "execution_count": 6,
      "metadata": {},
      "id": "c45be2c1"
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Date</th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Adj Close</th>\n      <th>Volume</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2020-01-02</td>\n      <td>46.860001</td>\n      <td>49.250000</td>\n      <td>46.630001</td>\n      <td>49.099998</td>\n      <td>49.099998</td>\n      <td>80331100</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2020-01-03</td>\n      <td>48.029999</td>\n      <td>49.389999</td>\n      <td>47.540001</td>\n      <td>48.599998</td>\n      <td>48.599998</td>\n      <td>73127400</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2020-01-06</td>\n      <td>48.020000</td>\n      <td>48.860001</td>\n      <td>47.860001</td>\n      <td>48.389999</td>\n      <td>48.389999</td>\n      <td>47934900</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2020-01-07</td>\n      <td>49.349998</td>\n      <td>49.389999</td>\n      <td>48.040001</td>\n      <td>48.250000</td>\n      <td>48.250000</td>\n      <td>58061400</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2020-01-08</td>\n      <td>47.849998</td>\n      <td>48.299999</td>\n      <td>47.139999</td>\n      <td>47.830002</td>\n      <td>47.830002</td>\n      <td>53767000</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "        Date       Open       High        Low      Close  Adj Close    Volume\n0 2020-01-02  46.860001  49.250000  46.630001  49.099998  49.099998  80331100\n1 2020-01-03  48.029999  49.389999  47.540001  48.599998  48.599998  73127400\n2 2020-01-06  48.020000  48.860001  47.860001  48.389999  48.389999  47934900\n3 2020-01-07  49.349998  49.389999  48.040001  48.250000  48.250000  58061400\n4 2020-01-08  47.849998  48.299999  47.139999  47.830002  47.830002  53767000"
          },
          "metadata": {}
        }
      ],
      "execution_count": 7,
      "metadata": {},
      "id": "67a37749"
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop('Date', axis=1)"
      ],
      "outputs": [],
      "execution_count": 8,
      "metadata": {},
      "id": "2362d32e"
    },
    {
      "cell_type": "code",
      "source": [
        "data = df.sample(frac=0.9)\n",
        "data_unseen = df.drop(data.index)\n",
        "\n",
        "data.reset_index(drop=True, inplace=True)\n",
        "data_unseen.reset_index(drop=True, inplace=True)\n",
        "\n",
        "print('Data for Modeling: ' + str(data.shape))\n",
        "print('Unseen Data For Predictions: ' + str(data_unseen.shape))"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data for Modeling: (454, 6)\n",
            "Unseen Data For Predictions: (51, 6)\n"
          ]
        }
      ],
      "execution_count": 9,
      "metadata": {},
      "id": "d8a5dfe8"
    },
    {
      "cell_type": "code",
      "source": [
        "from pycaret.regression import *\n",
        "exp_reg102 = setup(data=data, target='Adj Close', session_id=123,use_gpu=True)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": "<style type=\"text/css\">\n#T_d38c3_row16_col1, #T_d38c3_row42_col1 {\n  background-color: lightgreen;\n}\n</style>\n<table id=\"T_d38c3\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_d38c3_level0_col0\" class=\"col_heading level0 col0\" >Description</th>\n      <th id=\"T_d38c3_level0_col1\" class=\"col_heading level0 col1\" >Value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_d38c3_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_d38c3_row0_col0\" class=\"data row0 col0\" >session_id</td>\n      <td id=\"T_d38c3_row0_col1\" class=\"data row0 col1\" >123</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_d38c3_row1_col0\" class=\"data row1 col0\" >Target</td>\n      <td id=\"T_d38c3_row1_col1\" class=\"data row1 col1\" >Adj Close</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_d38c3_row2_col0\" class=\"data row2 col0\" >Original Data</td>\n      <td id=\"T_d38c3_row2_col1\" class=\"data row2 col1\" >(454, 6)</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_d38c3_row3_col0\" class=\"data row3 col0\" >Missing Values</td>\n      <td id=\"T_d38c3_row3_col1\" class=\"data row3 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_d38c3_row4_col0\" class=\"data row4 col0\" >Numeric Features</td>\n      <td id=\"T_d38c3_row4_col1\" class=\"data row4 col1\" >5</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n      <td id=\"T_d38c3_row5_col0\" class=\"data row5 col0\" >Categorical Features</td>\n      <td id=\"T_d38c3_row5_col1\" class=\"data row5 col1\" >0</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n      <td id=\"T_d38c3_row6_col0\" class=\"data row6 col0\" >Ordinal Features</td>\n      <td id=\"T_d38c3_row6_col1\" class=\"data row6 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n      <td id=\"T_d38c3_row7_col0\" class=\"data row7 col0\" >High Cardinality Features</td>\n      <td id=\"T_d38c3_row7_col1\" class=\"data row7 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n      <td id=\"T_d38c3_row8_col0\" class=\"data row8 col0\" >High Cardinality Method</td>\n      <td id=\"T_d38c3_row8_col1\" class=\"data row8 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n      <td id=\"T_d38c3_row9_col0\" class=\"data row9 col0\" >Transformed Train Set</td>\n      <td id=\"T_d38c3_row9_col1\" class=\"data row9 col1\" >(317, 1)</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n      <td id=\"T_d38c3_row10_col0\" class=\"data row10 col0\" >Transformed Test Set</td>\n      <td id=\"T_d38c3_row10_col1\" class=\"data row10 col1\" >(137, 1)</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n      <td id=\"T_d38c3_row11_col0\" class=\"data row11 col0\" >Shuffle Train-Test</td>\n      <td id=\"T_d38c3_row11_col1\" class=\"data row11 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n      <td id=\"T_d38c3_row12_col0\" class=\"data row12 col0\" >Stratify Train-Test</td>\n      <td id=\"T_d38c3_row12_col1\" class=\"data row12 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n      <td id=\"T_d38c3_row13_col0\" class=\"data row13 col0\" >Fold Generator</td>\n      <td id=\"T_d38c3_row13_col1\" class=\"data row13 col1\" >KFold</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n      <td id=\"T_d38c3_row14_col0\" class=\"data row14 col0\" >Fold Number</td>\n      <td id=\"T_d38c3_row14_col1\" class=\"data row14 col1\" >10</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n      <td id=\"T_d38c3_row15_col0\" class=\"data row15 col0\" >CPU Jobs</td>\n      <td id=\"T_d38c3_row15_col1\" class=\"data row15 col1\" >-1</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n      <td id=\"T_d38c3_row16_col0\" class=\"data row16 col0\" >Use GPU</td>\n      <td id=\"T_d38c3_row16_col1\" class=\"data row16 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n      <td id=\"T_d38c3_row17_col0\" class=\"data row17 col0\" >Log Experiment</td>\n      <td id=\"T_d38c3_row17_col1\" class=\"data row17 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n      <td id=\"T_d38c3_row18_col0\" class=\"data row18 col0\" >Experiment Name</td>\n      <td id=\"T_d38c3_row18_col1\" class=\"data row18 col1\" >reg-default-name</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n      <td id=\"T_d38c3_row19_col0\" class=\"data row19 col0\" >USI</td>\n      <td id=\"T_d38c3_row19_col1\" class=\"data row19 col1\" >21a0</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n      <td id=\"T_d38c3_row20_col0\" class=\"data row20 col0\" >Imputation Type</td>\n      <td id=\"T_d38c3_row20_col1\" class=\"data row20 col1\" >simple</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n      <td id=\"T_d38c3_row21_col0\" class=\"data row21 col0\" >Iterative Imputation Iteration</td>\n      <td id=\"T_d38c3_row21_col1\" class=\"data row21 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n      <td id=\"T_d38c3_row22_col0\" class=\"data row22 col0\" >Numeric Imputer</td>\n      <td id=\"T_d38c3_row22_col1\" class=\"data row22 col1\" >mean</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n      <td id=\"T_d38c3_row23_col0\" class=\"data row23 col0\" >Iterative Imputation Numeric Model</td>\n      <td id=\"T_d38c3_row23_col1\" class=\"data row23 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n      <td id=\"T_d38c3_row24_col0\" class=\"data row24 col0\" >Categorical Imputer</td>\n      <td id=\"T_d38c3_row24_col1\" class=\"data row24 col1\" >constant</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n      <td id=\"T_d38c3_row25_col0\" class=\"data row25 col0\" >Iterative Imputation Categorical Model</td>\n      <td id=\"T_d38c3_row25_col1\" class=\"data row25 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n      <td id=\"T_d38c3_row26_col0\" class=\"data row26 col0\" >Unknown Categoricals Handling</td>\n      <td id=\"T_d38c3_row26_col1\" class=\"data row26 col1\" >least_frequent</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n      <td id=\"T_d38c3_row27_col0\" class=\"data row27 col0\" >Normalize</td>\n      <td id=\"T_d38c3_row27_col1\" class=\"data row27 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n      <td id=\"T_d38c3_row28_col0\" class=\"data row28 col0\" >Normalize Method</td>\n      <td id=\"T_d38c3_row28_col1\" class=\"data row28 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n      <td id=\"T_d38c3_row29_col0\" class=\"data row29 col0\" >Transformation</td>\n      <td id=\"T_d38c3_row29_col1\" class=\"data row29 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n      <td id=\"T_d38c3_row30_col0\" class=\"data row30 col0\" >Transformation Method</td>\n      <td id=\"T_d38c3_row30_col1\" class=\"data row30 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n      <td id=\"T_d38c3_row31_col0\" class=\"data row31 col0\" >PCA</td>\n      <td id=\"T_d38c3_row31_col1\" class=\"data row31 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n      <td id=\"T_d38c3_row32_col0\" class=\"data row32 col0\" >PCA Method</td>\n      <td id=\"T_d38c3_row32_col1\" class=\"data row32 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n      <td id=\"T_d38c3_row33_col0\" class=\"data row33 col0\" >PCA Components</td>\n      <td id=\"T_d38c3_row33_col1\" class=\"data row33 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n      <td id=\"T_d38c3_row34_col0\" class=\"data row34 col0\" >Ignore Low Variance</td>\n      <td id=\"T_d38c3_row34_col1\" class=\"data row34 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n      <td id=\"T_d38c3_row35_col0\" class=\"data row35 col0\" >Combine Rare Levels</td>\n      <td id=\"T_d38c3_row35_col1\" class=\"data row35 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n      <td id=\"T_d38c3_row36_col0\" class=\"data row36 col0\" >Rare Level Threshold</td>\n      <td id=\"T_d38c3_row36_col1\" class=\"data row36 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n      <td id=\"T_d38c3_row37_col0\" class=\"data row37 col0\" >Numeric Binning</td>\n      <td id=\"T_d38c3_row37_col1\" class=\"data row37 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n      <td id=\"T_d38c3_row38_col0\" class=\"data row38 col0\" >Remove Outliers</td>\n      <td id=\"T_d38c3_row38_col1\" class=\"data row38 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n      <td id=\"T_d38c3_row39_col0\" class=\"data row39 col0\" >Outliers Threshold</td>\n      <td id=\"T_d38c3_row39_col1\" class=\"data row39 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n      <td id=\"T_d38c3_row40_col0\" class=\"data row40 col0\" >Remove Multicollinearity</td>\n      <td id=\"T_d38c3_row40_col1\" class=\"data row40 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n      <td id=\"T_d38c3_row41_col0\" class=\"data row41 col0\" >Multicollinearity Threshold</td>\n      <td id=\"T_d38c3_row41_col1\" class=\"data row41 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n      <td id=\"T_d38c3_row42_col0\" class=\"data row42 col0\" >Remove Perfect Collinearity</td>\n      <td id=\"T_d38c3_row42_col1\" class=\"data row42 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n      <td id=\"T_d38c3_row43_col0\" class=\"data row43 col0\" >Clustering</td>\n      <td id=\"T_d38c3_row43_col1\" class=\"data row43 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n      <td id=\"T_d38c3_row44_col0\" class=\"data row44 col0\" >Clustering Iteration</td>\n      <td id=\"T_d38c3_row44_col1\" class=\"data row44 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n      <td id=\"T_d38c3_row45_col0\" class=\"data row45 col0\" >Polynomial Features</td>\n      <td id=\"T_d38c3_row45_col1\" class=\"data row45 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n      <td id=\"T_d38c3_row46_col0\" class=\"data row46 col0\" >Polynomial Degree</td>\n      <td id=\"T_d38c3_row46_col1\" class=\"data row46 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n      <td id=\"T_d38c3_row47_col0\" class=\"data row47 col0\" >Trignometry Features</td>\n      <td id=\"T_d38c3_row47_col1\" class=\"data row47 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n      <td id=\"T_d38c3_row48_col0\" class=\"data row48 col0\" >Polynomial Threshold</td>\n      <td id=\"T_d38c3_row48_col1\" class=\"data row48 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n      <td id=\"T_d38c3_row49_col0\" class=\"data row49 col0\" >Group Features</td>\n      <td id=\"T_d38c3_row49_col1\" class=\"data row49 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n      <td id=\"T_d38c3_row50_col0\" class=\"data row50 col0\" >Feature Selection</td>\n      <td id=\"T_d38c3_row50_col1\" class=\"data row50 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n      <td id=\"T_d38c3_row51_col0\" class=\"data row51 col0\" >Feature Selection Method</td>\n      <td id=\"T_d38c3_row51_col1\" class=\"data row51 col1\" >classic</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n      <td id=\"T_d38c3_row52_col0\" class=\"data row52 col0\" >Features Selection Threshold</td>\n      <td id=\"T_d38c3_row52_col1\" class=\"data row52 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n      <td id=\"T_d38c3_row53_col0\" class=\"data row53 col0\" >Feature Interaction</td>\n      <td id=\"T_d38c3_row53_col1\" class=\"data row53 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n      <td id=\"T_d38c3_row54_col0\" class=\"data row54 col0\" >Feature Ratio</td>\n      <td id=\"T_d38c3_row54_col1\" class=\"data row54 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n      <td id=\"T_d38c3_row55_col0\" class=\"data row55 col0\" >Interaction Threshold</td>\n      <td id=\"T_d38c3_row55_col1\" class=\"data row55 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n      <td id=\"T_d38c3_row56_col0\" class=\"data row56 col0\" >Transform Target</td>\n      <td id=\"T_d38c3_row56_col1\" class=\"data row56 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_d38c3_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n      <td id=\"T_d38c3_row57_col0\" class=\"data row57 col0\" >Transform Target Method</td>\n      <td id=\"T_d38c3_row57_col1\" class=\"data row57 col1\" >box-cox</td>\n    </tr>\n  </tbody>\n</table>\n",
            "text/plain": "<pandas.io.formats.style.Styler at 0x1d95a37d4f0>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {},
      "id": "57f87d56"
    },
    {
      "cell_type": "code",
      "source": [
        "compare_models()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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#T_38c22_row15_col5, #T_38c22_row15_col6, #T_38c22_row16_col0, #T_38c22_row16_col1, #T_38c22_row16_col2, #T_38c22_row16_col3, #T_38c22_row16_col4, #T_38c22_row16_col5, #T_38c22_row16_col6, #T_38c22_row17_col0, #T_38c22_row17_col1, #T_38c22_row17_col2, #T_38c22_row17_col3, #T_38c22_row17_col4, #T_38c22_row17_col5, #T_38c22_row17_col6 {\n  text-align: left;\n}\n#T_38c22_row0_col1, #T_38c22_row0_col2, #T_38c22_row0_col3, #T_38c22_row0_col4, #T_38c22_row0_col5, #T_38c22_row1_col1, #T_38c22_row1_col2, #T_38c22_row1_col3, #T_38c22_row1_col4, #T_38c22_row1_col5, #T_38c22_row2_col6, #T_38c22_row3_col6, #T_38c22_row4_col6, #T_38c22_row5_col6, #T_38c22_row6_col6, #T_38c22_row7_col6, #T_38c22_row8_col6 {\n  text-align: left;\n  background-color: yellow;\n}\n#T_38c22_row0_col7, #T_38c22_row2_col7, #T_38c22_row3_col7, #T_38c22_row4_col7, #T_38c22_row5_col7, #T_38c22_row6_col7, #T_38c22_row7_col7, #T_38c22_row8_col7, #T_38c22_row9_col7, #T_38c22_row10_col7, #T_38c22_row11_col7, #T_38c22_row12_col7, #T_38c22_row13_col7, #T_38c22_row14_col7, #T_38c22_row15_col7, #T_38c22_row16_col7, #T_38c22_row17_col7 {\n  text-align: left;\n  background-color: lightgrey;\n}\n#T_38c22_row1_col7 {\n  text-align: left;\n  background-color: yellow;\n  background-color: lightgrey;\n}\n</style>\n<table id=\"T_38c22\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_38c22_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n      <th id=\"T_38c22_level0_col1\" class=\"col_heading level0 col1\" >MAE</th>\n      <th id=\"T_38c22_level0_col2\" class=\"col_heading level0 col2\" >MSE</th>\n      <th id=\"T_38c22_level0_col3\" class=\"col_heading level0 col3\" >RMSE</th>\n      <th id=\"T_38c22_level0_col4\" class=\"col_heading level0 col4\" >R2</th>\n      <th id=\"T_38c22_level0_col5\" class=\"col_heading level0 col5\" >RMSLE</th>\n      <th id=\"T_38c22_level0_col6\" class=\"col_heading level0 col6\" >MAPE</th>\n      <th id=\"T_38c22_level0_col7\" class=\"col_heading level0 col7\" >TT (Sec)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_38c22_level0_row0\" class=\"row_heading level0 row0\" >llar</th>\n      <td id=\"T_38c22_row0_col0\" class=\"data row0 col0\" >Lasso Least Angle Regression</td>\n      <td id=\"T_38c22_row0_col1\" class=\"data row0 col1\" >19.6847</td>\n      <td id=\"T_38c22_row0_col2\" class=\"data row0 col2\" >705.7987</td>\n      <td id=\"T_38c22_row0_col3\" class=\"data row0 col3\" >26.4243</td>\n      <td id=\"T_38c22_row0_col4\" class=\"data row0 col4\" >-0.0676</td>\n      <td id=\"T_38c22_row0_col5\" class=\"data row0 col5\" >0.3158</td>\n      <td id=\"T_38c22_row0_col6\" class=\"data row0 col6\" >0.2678</td>\n      <td id=\"T_38c22_row0_col7\" class=\"data row0 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row1\" class=\"row_heading level0 row1\" >dummy</th>\n      <td id=\"T_38c22_row1_col0\" class=\"data row1 col0\" >Dummy Regressor</td>\n      <td id=\"T_38c22_row1_col1\" class=\"data row1 col1\" >19.6847</td>\n      <td id=\"T_38c22_row1_col2\" class=\"data row1 col2\" >705.7987</td>\n      <td id=\"T_38c22_row1_col3\" class=\"data row1 col3\" >26.4243</td>\n      <td id=\"T_38c22_row1_col4\" class=\"data row1 col4\" >-0.0676</td>\n      <td id=\"T_38c22_row1_col5\" class=\"data row1 col5\" >0.3158</td>\n      <td id=\"T_38c22_row1_col6\" class=\"data row1 col6\" >0.2678</td>\n      <td id=\"T_38c22_row1_col7\" class=\"data row1 col7\" >0.0020</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row2\" class=\"row_heading level0 row2\" >lasso</th>\n      <td id=\"T_38c22_row2_col0\" class=\"data row2 col0\" >Lasso Regression</td>\n      <td id=\"T_38c22_row2_col1\" class=\"data row2 col1\" >19.7050</td>\n      <td id=\"T_38c22_row2_col2\" class=\"data row2 col2\" >709.5984</td>\n      <td id=\"T_38c22_row2_col3\" class=\"data row2 col3\" >26.5288</td>\n      <td id=\"T_38c22_row2_col4\" class=\"data row2 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row2_col5\" class=\"data row2 col5\" >0.3159</td>\n      <td id=\"T_38c22_row2_col6\" class=\"data row2 col6\" >0.2659</td>\n      <td id=\"T_38c22_row2_col7\" class=\"data row2 col7\" >0.0050</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row3\" class=\"row_heading level0 row3\" >ridge</th>\n      <td id=\"T_38c22_row3_col0\" class=\"data row3 col0\" >Ridge Regression</td>\n      <td id=\"T_38c22_row3_col1\" class=\"data row3 col1\" >19.7050</td>\n      <td id=\"T_38c22_row3_col2\" class=\"data row3 col2\" >709.5984</td>\n      <td id=\"T_38c22_row3_col3\" class=\"data row3 col3\" >26.5288</td>\n      <td id=\"T_38c22_row3_col4\" class=\"data row3 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row3_col5\" class=\"data row3 col5\" >0.3159</td>\n      <td id=\"T_38c22_row3_col6\" class=\"data row3 col6\" >0.2659</td>\n      <td id=\"T_38c22_row3_col7\" class=\"data row3 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row4\" class=\"row_heading level0 row4\" >en</th>\n      <td id=\"T_38c22_row4_col0\" class=\"data row4 col0\" >Elastic Net</td>\n      <td id=\"T_38c22_row4_col1\" class=\"data row4 col1\" >19.7050</td>\n      <td id=\"T_38c22_row4_col2\" class=\"data row4 col2\" >709.5984</td>\n      <td id=\"T_38c22_row4_col3\" class=\"data row4 col3\" >26.5288</td>\n      <td id=\"T_38c22_row4_col4\" class=\"data row4 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row4_col5\" class=\"data row4 col5\" >0.3159</td>\n      <td id=\"T_38c22_row4_col6\" class=\"data row4 col6\" >0.2659</td>\n      <td id=\"T_38c22_row4_col7\" class=\"data row4 col7\" >0.0050</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row5\" class=\"row_heading level0 row5\" >lar</th>\n      <td id=\"T_38c22_row5_col0\" class=\"data row5 col0\" >Least Angle Regression</td>\n      <td id=\"T_38c22_row5_col1\" class=\"data row5 col1\" >19.7050</td>\n      <td id=\"T_38c22_row5_col2\" class=\"data row5 col2\" >709.5984</td>\n      <td id=\"T_38c22_row5_col3\" class=\"data row5 col3\" >26.5288</td>\n      <td id=\"T_38c22_row5_col4\" class=\"data row5 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row5_col5\" class=\"data row5 col5\" >0.3159</td>\n      <td id=\"T_38c22_row5_col6\" class=\"data row5 col6\" >0.2659</td>\n      <td id=\"T_38c22_row5_col7\" class=\"data row5 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row6\" class=\"row_heading level0 row6\" >omp</th>\n      <td id=\"T_38c22_row6_col0\" class=\"data row6 col0\" >Orthogonal Matching Pursuit</td>\n      <td id=\"T_38c22_row6_col1\" class=\"data row6 col1\" >19.7050</td>\n      <td id=\"T_38c22_row6_col2\" class=\"data row6 col2\" >709.5984</td>\n      <td id=\"T_38c22_row6_col3\" class=\"data row6 col3\" >26.5288</td>\n      <td id=\"T_38c22_row6_col4\" class=\"data row6 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row6_col5\" class=\"data row6 col5\" >0.3159</td>\n      <td id=\"T_38c22_row6_col6\" class=\"data row6 col6\" >0.2659</td>\n      <td id=\"T_38c22_row6_col7\" class=\"data row6 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row7\" class=\"row_heading level0 row7\" >br</th>\n      <td id=\"T_38c22_row7_col0\" class=\"data row7 col0\" >Bayesian Ridge</td>\n      <td id=\"T_38c22_row7_col1\" class=\"data row7 col1\" >19.7050</td>\n      <td id=\"T_38c22_row7_col2\" class=\"data row7 col2\" >709.5984</td>\n      <td id=\"T_38c22_row7_col3\" class=\"data row7 col3\" >26.5288</td>\n      <td id=\"T_38c22_row7_col4\" class=\"data row7 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row7_col5\" class=\"data row7 col5\" >0.3159</td>\n      <td id=\"T_38c22_row7_col6\" class=\"data row7 col6\" >0.2659</td>\n      <td id=\"T_38c22_row7_col7\" class=\"data row7 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row8\" class=\"row_heading level0 row8\" >lr</th>\n      <td id=\"T_38c22_row8_col0\" class=\"data row8 col0\" >Linear Regression</td>\n      <td id=\"T_38c22_row8_col1\" class=\"data row8 col1\" >19.7050</td>\n      <td id=\"T_38c22_row8_col2\" class=\"data row8 col2\" >709.5984</td>\n      <td id=\"T_38c22_row8_col3\" class=\"data row8 col3\" >26.5288</td>\n      <td id=\"T_38c22_row8_col4\" class=\"data row8 col4\" >-0.0792</td>\n      <td id=\"T_38c22_row8_col5\" class=\"data row8 col5\" >0.3159</td>\n      <td id=\"T_38c22_row8_col6\" class=\"data row8 col6\" >0.2659</td>\n      <td id=\"T_38c22_row8_col7\" class=\"data row8 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row9\" class=\"row_heading level0 row9\" >ada</th>\n      <td id=\"T_38c22_row9_col0\" class=\"data row9 col0\" >AdaBoost Regressor</td>\n      <td id=\"T_38c22_row9_col1\" class=\"data row9 col1\" >20.8012</td>\n      <td id=\"T_38c22_row9_col2\" class=\"data row9 col2\" >743.6255</td>\n      <td id=\"T_38c22_row9_col3\" class=\"data row9 col3\" >27.2129</td>\n      <td id=\"T_38c22_row9_col4\" class=\"data row9 col4\" >-0.1522</td>\n      <td id=\"T_38c22_row9_col5\" class=\"data row9 col5\" >0.3269</td>\n      <td id=\"T_38c22_row9_col6\" class=\"data row9 col6\" >0.2886</td>\n      <td id=\"T_38c22_row9_col7\" class=\"data row9 col7\" >0.0150</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row10\" class=\"row_heading level0 row10\" >lightgbm</th>\n      <td id=\"T_38c22_row10_col0\" class=\"data row10 col0\" >Light Gradient Boosting Machine</td>\n      <td id=\"T_38c22_row10_col1\" class=\"data row10 col1\" >21.0255</td>\n      <td id=\"T_38c22_row10_col2\" class=\"data row10 col2\" >754.5424</td>\n      <td id=\"T_38c22_row10_col3\" class=\"data row10 col3\" >27.3560</td>\n      <td id=\"T_38c22_row10_col4\" class=\"data row10 col4\" >-0.1523</td>\n      <td id=\"T_38c22_row10_col5\" class=\"data row10 col5\" >0.3244</td>\n      <td id=\"T_38c22_row10_col6\" class=\"data row10 col6\" >0.2789</td>\n      <td id=\"T_38c22_row10_col7\" class=\"data row10 col7\" >0.2880</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row11\" class=\"row_heading level0 row11\" >gbr</th>\n      <td id=\"T_38c22_row11_col0\" class=\"data row11 col0\" >Gradient Boosting Regressor</td>\n      <td id=\"T_38c22_row11_col1\" class=\"data row11 col1\" >21.0842</td>\n      <td id=\"T_38c22_row11_col2\" class=\"data row11 col2\" >812.9401</td>\n      <td id=\"T_38c22_row11_col3\" class=\"data row11 col3\" >28.3323</td>\n      <td id=\"T_38c22_row11_col4\" class=\"data row11 col4\" >-0.2529</td>\n      <td id=\"T_38c22_row11_col5\" class=\"data row11 col5\" >0.3320</td>\n      <td id=\"T_38c22_row11_col6\" class=\"data row11 col6\" >0.2768</td>\n      <td id=\"T_38c22_row11_col7\" class=\"data row11 col7\" >0.0260</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row12\" class=\"row_heading level0 row12\" >knn</th>\n      <td id=\"T_38c22_row12_col0\" class=\"data row12 col0\" >K Neighbors Regressor</td>\n      <td id=\"T_38c22_row12_col1\" class=\"data row12 col1\" >21.8658</td>\n      <td id=\"T_38c22_row12_col2\" class=\"data row12 col2\" >814.6265</td>\n      <td id=\"T_38c22_row12_col3\" class=\"data row12 col3\" >28.4186</td>\n      <td id=\"T_38c22_row12_col4\" class=\"data row12 col4\" >-0.2598</td>\n      <td id=\"T_38c22_row12_col5\" class=\"data row12 col5\" >0.3370</td>\n      <td id=\"T_38c22_row12_col6\" class=\"data row12 col6\" >0.2898</td>\n      <td id=\"T_38c22_row12_col7\" class=\"data row12 col7\" >0.2290</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row13\" class=\"row_heading level0 row13\" >rf</th>\n      <td id=\"T_38c22_row13_col0\" class=\"data row13 col0\" >Random Forest Regressor</td>\n      <td id=\"T_38c22_row13_col1\" class=\"data row13 col1\" >23.4239</td>\n      <td id=\"T_38c22_row13_col2\" class=\"data row13 col2\" >982.0650</td>\n      <td id=\"T_38c22_row13_col3\" class=\"data row13 col3\" >31.0299</td>\n      <td id=\"T_38c22_row13_col4\" class=\"data row13 col4\" >-0.5242</td>\n      <td id=\"T_38c22_row13_col5\" class=\"data row13 col5\" >0.3630</td>\n      <td id=\"T_38c22_row13_col6\" class=\"data row13 col6\" >0.3049</td>\n      <td id=\"T_38c22_row13_col7\" class=\"data row13 col7\" >0.2830</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row14\" class=\"row_heading level0 row14\" >et</th>\n      <td id=\"T_38c22_row14_col0\" class=\"data row14 col0\" >Extra Trees Regressor</td>\n      <td id=\"T_38c22_row14_col1\" class=\"data row14 col1\" >24.3365</td>\n      <td id=\"T_38c22_row14_col2\" class=\"data row14 col2\" >1058.6766</td>\n      <td id=\"T_38c22_row14_col3\" class=\"data row14 col3\" >32.2092</td>\n      <td id=\"T_38c22_row14_col4\" class=\"data row14 col4\" >-0.6553</td>\n      <td id=\"T_38c22_row14_col5\" class=\"data row14 col5\" >0.3822</td>\n      <td id=\"T_38c22_row14_col6\" class=\"data row14 col6\" >0.3133</td>\n      <td id=\"T_38c22_row14_col7\" class=\"data row14 col7\" >0.2810</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row15\" class=\"row_heading level0 row15\" >dt</th>\n      <td id=\"T_38c22_row15_col0\" class=\"data row15 col0\" >Decision Tree Regressor</td>\n      <td id=\"T_38c22_row15_col1\" class=\"data row15 col1\" >26.7733</td>\n      <td id=\"T_38c22_row15_col2\" class=\"data row15 col2\" >1330.4869</td>\n      <td id=\"T_38c22_row15_col3\" class=\"data row15 col3\" >36.0427</td>\n      <td id=\"T_38c22_row15_col4\" class=\"data row15 col4\" >-1.1042</td>\n      <td id=\"T_38c22_row15_col5\" class=\"data row15 col5\" >0.4243</td>\n      <td id=\"T_38c22_row15_col6\" class=\"data row15 col6\" >0.3448</td>\n      <td id=\"T_38c22_row15_col7\" class=\"data row15 col7\" >0.0040</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row16\" class=\"row_heading level0 row16\" >huber</th>\n      <td id=\"T_38c22_row16_col0\" class=\"data row16 col0\" >Huber Regressor</td>\n      <td id=\"T_38c22_row16_col1\" class=\"data row16 col1\" >33.7082</td>\n      <td id=\"T_38c22_row16_col2\" class=\"data row16 col2\" >1912.2304</td>\n      <td id=\"T_38c22_row16_col3\" class=\"data row16 col3\" >42.4051</td>\n      <td id=\"T_38c22_row16_col4\" class=\"data row16 col4\" >-2.1056</td>\n      <td id=\"T_38c22_row16_col5\" class=\"data row16 col5\" >0.4900</td>\n      <td id=\"T_38c22_row16_col6\" class=\"data row16 col6\" >0.4431</td>\n      <td id=\"T_38c22_row16_col7\" class=\"data row16 col7\" >0.0090</td>\n    </tr>\n    <tr>\n      <th id=\"T_38c22_level0_row17\" class=\"row_heading level0 row17\" >par</th>\n      <td id=\"T_38c22_row17_col0\" class=\"data row17 col0\" >Passive Aggressive Regressor</td>\n      <td id=\"T_38c22_row17_col1\" class=\"data row17 col1\" >46.8672</td>\n      <td id=\"T_38c22_row17_col2\" class=\"data row17 col2\" >4181.8742</td>\n      <td id=\"T_38c22_row17_col3\" class=\"data row17 col3\" >62.2584</td>\n      <td id=\"T_38c22_row17_col4\" class=\"data row17 col4\" >-5.3686</td>\n      <td id=\"T_38c22_row17_col5\" class=\"data row17 col5\" >0.6470</td>\n      <td id=\"T_38c22_row17_col6\" class=\"data row17 col6\" >0.6687</td>\n      <td id=\"T_38c22_row17_col7\" class=\"data row17 col7\" >0.0040</td>\n    </tr>\n  </tbody>\n</table>\n",
            "text/plain": "<pandas.io.formats.style.Styler at 0x1d959e80e80>"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "execution_count": 11,
          "data": {
            "text/plain": "LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,\n          fit_path=True, jitter=None, max_iter=500, normalize=True,\n          positive=False, precompute='auto', random_state=123, verbose=False)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 11,
      "metadata": {},
      "id": "5909a48d"
    },
    {
      "cell_type": "code",
      "source": [
        "lr = create_model('lr')"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": "<style type=\"text/css\">\n#T_7f40c_row10_col0, #T_7f40c_row10_col1, #T_7f40c_row10_col2, #T_7f40c_row10_col3, #T_7f40c_row10_col4, #T_7f40c_row10_col5 {\n  background: yellow;\n}\n</style>\n<table id=\"T_7f40c\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_7f40c_level0_col0\" class=\"col_heading level0 col0\" >MAE</th>\n      <th id=\"T_7f40c_level0_col1\" class=\"col_heading level0 col1\" >MSE</th>\n      <th id=\"T_7f40c_level0_col2\" class=\"col_heading level0 col2\" >RMSE</th>\n      <th id=\"T_7f40c_level0_col3\" class=\"col_heading level0 col3\" >R2</th>\n      <th id=\"T_7f40c_level0_col4\" class=\"col_heading level0 col4\" >RMSLE</th>\n      <th id=\"T_7f40c_level0_col5\" class=\"col_heading level0 col5\" >MAPE</th>\n    </tr>\n    <tr>\n      <th class=\"index_name level0\" >Fold</th>\n      <th class=\"blank col0\" >&nbsp;</th>\n      <th class=\"blank col1\" >&nbsp;</th>\n      <th class=\"blank col2\" >&nbsp;</th>\n      <th class=\"blank col3\" >&nbsp;</th>\n      <th class=\"blank col4\" >&nbsp;</th>\n      <th class=\"blank col5\" >&nbsp;</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_7f40c_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_7f40c_row0_col0\" class=\"data row0 col0\" >23.3505</td>\n      <td id=\"T_7f40c_row0_col1\" class=\"data row0 col1\" >829.1060</td>\n      <td id=\"T_7f40c_row0_col2\" class=\"data row0 col2\" >28.7942</td>\n      <td id=\"T_7f40c_row0_col3\" class=\"data row0 col3\" >0.0182</td>\n      <td id=\"T_7f40c_row0_col4\" class=\"data row0 col4\" >0.3516</td>\n      <td id=\"T_7f40c_row0_col5\" class=\"data row0 col5\" >0.3242</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_7f40c_row1_col0\" class=\"data row1 col0\" >20.0636</td>\n      <td id=\"T_7f40c_row1_col1\" class=\"data row1 col1\" >744.3257</td>\n      <td id=\"T_7f40c_row1_col2\" class=\"data row1 col2\" >27.2823</td>\n      <td id=\"T_7f40c_row1_col3\" class=\"data row1 col3\" >-0.0662</td>\n      <td id=\"T_7f40c_row1_col4\" class=\"data row1 col4\" >0.2964</td>\n      <td id=\"T_7f40c_row1_col5\" class=\"data row1 col5\" >0.2311</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_7f40c_row2_col0\" class=\"data row2 col0\" >18.0652</td>\n      <td id=\"T_7f40c_row2_col1\" class=\"data row2 col1\" >513.7551</td>\n      <td id=\"T_7f40c_row2_col2\" class=\"data row2 col2\" >22.6662</td>\n      <td id=\"T_7f40c_row2_col3\" class=\"data row2 col3\" >-0.1731</td>\n      <td id=\"T_7f40c_row2_col4\" class=\"data row2 col4\" >0.3244</td>\n      <td id=\"T_7f40c_row2_col5\" class=\"data row2 col5\" >0.3043</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_7f40c_row3_col0\" class=\"data row3 col0\" >14.2674</td>\n      <td id=\"T_7f40c_row3_col1\" class=\"data row3 col1\" >477.3210</td>\n      <td id=\"T_7f40c_row3_col2\" class=\"data row3 col2\" >21.8477</td>\n      <td id=\"T_7f40c_row3_col3\" class=\"data row3 col3\" >-0.1561</td>\n      <td id=\"T_7f40c_row3_col4\" class=\"data row3 col4\" >0.2556</td>\n      <td id=\"T_7f40c_row3_col5\" class=\"data row3 col5\" >0.1832</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_7f40c_row4_col0\" class=\"data row4 col0\" >18.3087</td>\n      <td id=\"T_7f40c_row4_col1\" class=\"data row4 col1\" >742.9083</td>\n      <td id=\"T_7f40c_row4_col2\" class=\"data row4 col2\" >27.2563</td>\n      <td id=\"T_7f40c_row4_col3\" class=\"data row4 col3\" >0.0198</td>\n      <td id=\"T_7f40c_row4_col4\" class=\"data row4 col4\" >0.3238</td>\n      <td id=\"T_7f40c_row4_col5\" class=\"data row4 col5\" >0.2556</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n      <td id=\"T_7f40c_row5_col0\" class=\"data row5 col0\" >22.0040</td>\n      <td id=\"T_7f40c_row5_col1\" class=\"data row5 col1\" >864.9231</td>\n      <td id=\"T_7f40c_row5_col2\" class=\"data row5 col2\" >29.4096</td>\n      <td id=\"T_7f40c_row5_col3\" class=\"data row5 col3\" >-0.0452</td>\n      <td id=\"T_7f40c_row5_col4\" class=\"data row5 col4\" >0.3291</td>\n      <td id=\"T_7f40c_row5_col5\" class=\"data row5 col5\" >0.2680</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n      <td id=\"T_7f40c_row6_col0\" class=\"data row6 col0\" >19.8910</td>\n      <td id=\"T_7f40c_row6_col1\" class=\"data row6 col1\" >839.6346</td>\n      <td id=\"T_7f40c_row6_col2\" class=\"data row6 col2\" >28.9764</td>\n      <td id=\"T_7f40c_row6_col3\" class=\"data row6 col3\" >-0.1504</td>\n      <td id=\"T_7f40c_row6_col4\" class=\"data row6 col4\" >0.2980</td>\n      <td id=\"T_7f40c_row6_col5\" class=\"data row6 col5\" >0.2098</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n      <td id=\"T_7f40c_row7_col0\" class=\"data row7 col0\" >20.1125</td>\n      <td id=\"T_7f40c_row7_col1\" class=\"data row7 col1\" >675.4976</td>\n      <td id=\"T_7f40c_row7_col2\" class=\"data row7 col2\" >25.9903</td>\n      <td id=\"T_7f40c_row7_col3\" class=\"data row7 col3\" >-0.0666</td>\n      <td id=\"T_7f40c_row7_col4\" class=\"data row7 col4\" >0.3205</td>\n      <td id=\"T_7f40c_row7_col5\" class=\"data row7 col5\" >0.2887</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n      <td id=\"T_7f40c_row8_col0\" class=\"data row8 col0\" >22.7331</td>\n      <td id=\"T_7f40c_row8_col1\" class=\"data row8 col1\" >733.1327</td>\n      <td id=\"T_7f40c_row8_col2\" class=\"data row8 col2\" >27.0764</td>\n      <td id=\"T_7f40c_row8_col3\" class=\"data row8 col3\" >-0.1392</td>\n      <td id=\"T_7f40c_row8_col4\" class=\"data row8 col4\" >0.3731</td>\n      <td id=\"T_7f40c_row8_col5\" class=\"data row8 col5\" >0.3742</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n      <td id=\"T_7f40c_row9_col0\" class=\"data row9 col0\" >18.2541</td>\n      <td id=\"T_7f40c_row9_col1\" class=\"data row9 col1\" >675.3796</td>\n      <td id=\"T_7f40c_row9_col2\" class=\"data row9 col2\" >25.9881</td>\n      <td id=\"T_7f40c_row9_col3\" class=\"data row9 col3\" >-0.0333</td>\n      <td id=\"T_7f40c_row9_col4\" class=\"data row9 col4\" >0.2860</td>\n      <td id=\"T_7f40c_row9_col5\" class=\"data row9 col5\" >0.2198</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n      <td id=\"T_7f40c_row10_col0\" class=\"data row10 col0\" >19.7050</td>\n      <td id=\"T_7f40c_row10_col1\" class=\"data row10 col1\" >709.5984</td>\n      <td id=\"T_7f40c_row10_col2\" class=\"data row10 col2\" >26.5288</td>\n      <td id=\"T_7f40c_row10_col3\" class=\"data row10 col3\" >-0.0792</td>\n      <td id=\"T_7f40c_row10_col4\" class=\"data row10 col4\" >0.3159</td>\n      <td id=\"T_7f40c_row10_col5\" class=\"data row10 col5\" >0.2659</td>\n    </tr>\n    <tr>\n      <th id=\"T_7f40c_level0_row11\" class=\"row_heading level0 row11\" >Std</th>\n      <td id=\"T_7f40c_row11_col0\" class=\"data row11 col0\" >2.5374</td>\n      <td id=\"T_7f40c_row11_col1\" class=\"data row11 col1\" >123.6236</td>\n      <td id=\"T_7f40c_row11_col2\" class=\"data row11 col2\" >2.4132</td>\n      <td id=\"T_7f40c_row11_col3\" class=\"data row11 col3\" >0.0680</td>\n      <td id=\"T_7f40c_row11_col4\" class=\"data row11 col4\" >0.0318</td>\n      <td id=\"T_7f40c_row11_col5\" class=\"data row11 col5\" >0.0553</td>\n    </tr>\n  </tbody>\n</table>\n",
            "text/plain": "<pandas.io.formats.style.Styler at 0x1d95a6f5610>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 12,
      "metadata": {},
      "id": "9760584e"
    },
    {
      "cell_type": "code",
      "source": [
        "tuned_lr = tune_model(lr, n_iter=1000)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": "<style type=\"text/css\">\n#T_71e04_row10_col0, #T_71e04_row10_col1, #T_71e04_row10_col2, #T_71e04_row10_col3, #T_71e04_row10_col4, #T_71e04_row10_col5 {\n  background: yellow;\n}\n</style>\n<table id=\"T_71e04\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_71e04_level0_col0\" class=\"col_heading level0 col0\" >MAE</th>\n      <th id=\"T_71e04_level0_col1\" class=\"col_heading level0 col1\" >MSE</th>\n      <th id=\"T_71e04_level0_col2\" class=\"col_heading level0 col2\" >RMSE</th>\n      <th id=\"T_71e04_level0_col3\" class=\"col_heading level0 col3\" >R2</th>\n      <th id=\"T_71e04_level0_col4\" class=\"col_heading level0 col4\" >RMSLE</th>\n      <th id=\"T_71e04_level0_col5\" class=\"col_heading level0 col5\" >MAPE</th>\n    </tr>\n    <tr>\n      <th class=\"index_name level0\" >Fold</th>\n      <th class=\"blank col0\" >&nbsp;</th>\n      <th class=\"blank col1\" >&nbsp;</th>\n      <th class=\"blank col2\" >&nbsp;</th>\n      <th class=\"blank col3\" >&nbsp;</th>\n      <th class=\"blank col4\" >&nbsp;</th>\n      <th class=\"blank col5\" >&nbsp;</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_71e04_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_71e04_row0_col0\" class=\"data row0 col0\" >23.3505</td>\n      <td id=\"T_71e04_row0_col1\" class=\"data row0 col1\" >829.1060</td>\n      <td id=\"T_71e04_row0_col2\" class=\"data row0 col2\" >28.7942</td>\n      <td id=\"T_71e04_row0_col3\" class=\"data row0 col3\" >0.0182</td>\n      <td id=\"T_71e04_row0_col4\" class=\"data row0 col4\" >0.3516</td>\n      <td id=\"T_71e04_row0_col5\" class=\"data row0 col5\" >0.3242</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_71e04_row1_col0\" class=\"data row1 col0\" >20.0636</td>\n      <td id=\"T_71e04_row1_col1\" class=\"data row1 col1\" >744.3257</td>\n      <td id=\"T_71e04_row1_col2\" class=\"data row1 col2\" >27.2823</td>\n      <td id=\"T_71e04_row1_col3\" class=\"data row1 col3\" >-0.0662</td>\n      <td id=\"T_71e04_row1_col4\" class=\"data row1 col4\" >0.2964</td>\n      <td id=\"T_71e04_row1_col5\" class=\"data row1 col5\" >0.2311</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_71e04_row2_col0\" class=\"data row2 col0\" >18.0652</td>\n      <td id=\"T_71e04_row2_col1\" class=\"data row2 col1\" >513.7551</td>\n      <td id=\"T_71e04_row2_col2\" class=\"data row2 col2\" >22.6662</td>\n      <td id=\"T_71e04_row2_col3\" class=\"data row2 col3\" >-0.1731</td>\n      <td id=\"T_71e04_row2_col4\" class=\"data row2 col4\" >0.3244</td>\n      <td id=\"T_71e04_row2_col5\" class=\"data row2 col5\" >0.3043</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_71e04_row3_col0\" class=\"data row3 col0\" >14.2674</td>\n      <td id=\"T_71e04_row3_col1\" class=\"data row3 col1\" >477.3210</td>\n      <td id=\"T_71e04_row3_col2\" class=\"data row3 col2\" >21.8477</td>\n      <td id=\"T_71e04_row3_col3\" class=\"data row3 col3\" >-0.1561</td>\n      <td id=\"T_71e04_row3_col4\" class=\"data row3 col4\" >0.2556</td>\n      <td id=\"T_71e04_row3_col5\" class=\"data row3 col5\" >0.1832</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_71e04_row4_col0\" class=\"data row4 col0\" >18.3087</td>\n      <td id=\"T_71e04_row4_col1\" class=\"data row4 col1\" >742.9083</td>\n      <td id=\"T_71e04_row4_col2\" class=\"data row4 col2\" >27.2563</td>\n      <td id=\"T_71e04_row4_col3\" class=\"data row4 col3\" >0.0198</td>\n      <td id=\"T_71e04_row4_col4\" class=\"data row4 col4\" >0.3238</td>\n      <td id=\"T_71e04_row4_col5\" class=\"data row4 col5\" >0.2556</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n      <td id=\"T_71e04_row5_col0\" class=\"data row5 col0\" >22.0040</td>\n      <td id=\"T_71e04_row5_col1\" class=\"data row5 col1\" >864.9231</td>\n      <td id=\"T_71e04_row5_col2\" class=\"data row5 col2\" >29.4096</td>\n      <td id=\"T_71e04_row5_col3\" class=\"data row5 col3\" >-0.0452</td>\n      <td id=\"T_71e04_row5_col4\" class=\"data row5 col4\" >0.3291</td>\n      <td id=\"T_71e04_row5_col5\" class=\"data row5 col5\" >0.2680</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n      <td id=\"T_71e04_row6_col0\" class=\"data row6 col0\" >19.8910</td>\n      <td id=\"T_71e04_row6_col1\" class=\"data row6 col1\" >839.6346</td>\n      <td id=\"T_71e04_row6_col2\" class=\"data row6 col2\" >28.9764</td>\n      <td id=\"T_71e04_row6_col3\" class=\"data row6 col3\" >-0.1504</td>\n      <td id=\"T_71e04_row6_col4\" class=\"data row6 col4\" >0.2980</td>\n      <td id=\"T_71e04_row6_col5\" class=\"data row6 col5\" >0.2098</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n      <td id=\"T_71e04_row7_col0\" class=\"data row7 col0\" >20.1125</td>\n      <td id=\"T_71e04_row7_col1\" class=\"data row7 col1\" >675.4976</td>\n      <td id=\"T_71e04_row7_col2\" class=\"data row7 col2\" >25.9903</td>\n      <td id=\"T_71e04_row7_col3\" class=\"data row7 col3\" >-0.0666</td>\n      <td id=\"T_71e04_row7_col4\" class=\"data row7 col4\" >0.3205</td>\n      <td id=\"T_71e04_row7_col5\" class=\"data row7 col5\" >0.2887</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n      <td id=\"T_71e04_row8_col0\" class=\"data row8 col0\" >22.7331</td>\n      <td id=\"T_71e04_row8_col1\" class=\"data row8 col1\" >733.1327</td>\n      <td id=\"T_71e04_row8_col2\" class=\"data row8 col2\" >27.0764</td>\n      <td id=\"T_71e04_row8_col3\" class=\"data row8 col3\" >-0.1392</td>\n      <td id=\"T_71e04_row8_col4\" class=\"data row8 col4\" >0.3731</td>\n      <td id=\"T_71e04_row8_col5\" class=\"data row8 col5\" >0.3742</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n      <td id=\"T_71e04_row9_col0\" class=\"data row9 col0\" >18.2541</td>\n      <td id=\"T_71e04_row9_col1\" class=\"data row9 col1\" >675.3796</td>\n      <td id=\"T_71e04_row9_col2\" class=\"data row9 col2\" >25.9881</td>\n      <td id=\"T_71e04_row9_col3\" class=\"data row9 col3\" >-0.0333</td>\n      <td id=\"T_71e04_row9_col4\" class=\"data row9 col4\" >0.2860</td>\n      <td id=\"T_71e04_row9_col5\" class=\"data row9 col5\" >0.2198</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n      <td id=\"T_71e04_row10_col0\" class=\"data row10 col0\" >19.7050</td>\n      <td id=\"T_71e04_row10_col1\" class=\"data row10 col1\" >709.5984</td>\n      <td id=\"T_71e04_row10_col2\" class=\"data row10 col2\" >26.5288</td>\n      <td id=\"T_71e04_row10_col3\" class=\"data row10 col3\" >-0.0792</td>\n      <td id=\"T_71e04_row10_col4\" class=\"data row10 col4\" >0.3159</td>\n      <td id=\"T_71e04_row10_col5\" class=\"data row10 col5\" >0.2659</td>\n    </tr>\n    <tr>\n      <th id=\"T_71e04_level0_row11\" class=\"row_heading level0 row11\" >Std</th>\n      <td id=\"T_71e04_row11_col0\" class=\"data row11 col0\" >2.5374</td>\n      <td id=\"T_71e04_row11_col1\" class=\"data row11 col1\" >123.6235</td>\n      <td id=\"T_71e04_row11_col2\" class=\"data row11 col2\" >2.4132</td>\n      <td id=\"T_71e04_row11_col3\" class=\"data row11 col3\" >0.0680</td>\n      <td id=\"T_71e04_row11_col4\" class=\"data row11 col4\" >0.0318</td>\n      <td id=\"T_71e04_row11_col5\" class=\"data row11 col5\" >0.0553</td>\n    </tr>\n  </tbody>\n</table>\n",
            "text/plain": "<pandas.io.formats.style.Styler at 0x1d959ebbbb0>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 13,
      "metadata": {},
      "id": "c5cb84ea"
    },
    {
      "cell_type": "code",
      "source": [
        "unseen_predictions = predict_model(tuned_lr, data=data_unseen)\n",
        "unseen_predictions"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_4dbba\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_4dbba_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n      <th id=\"T_4dbba_level0_col1\" class=\"col_heading level0 col1\" >MAE</th>\n      <th id=\"T_4dbba_level0_col2\" class=\"col_heading level0 col2\" >MSE</th>\n      <th id=\"T_4dbba_level0_col3\" class=\"col_heading level0 col3\" >RMSE</th>\n      <th id=\"T_4dbba_level0_col4\" class=\"col_heading level0 col4\" >R2</th>\n      <th id=\"T_4dbba_level0_col5\" class=\"col_heading level0 col5\" >RMSLE</th>\n      <th id=\"T_4dbba_level0_col6\" class=\"col_heading level0 col6\" >MAPE</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_4dbba_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_4dbba_row0_col0\" class=\"data row0 col0\" >Linear Regression</td>\n      <td id=\"T_4dbba_row0_col1\" class=\"data row0 col1\" >19.1215</td>\n      <td id=\"T_4dbba_row0_col2\" class=\"data row0 col2\" >707.3923</td>\n      <td id=\"T_4dbba_row0_col3\" class=\"data row0 col3\" >26.5968</td>\n      <td id=\"T_4dbba_row0_col4\" class=\"data row0 col4\" >0.0169</td>\n      <td id=\"T_4dbba_row0_col5\" class=\"data row0 col5\" >0.3190</td>\n      <td id=\"T_4dbba_row0_col6\" class=\"data row0 col6\" >0.2668</td>\n    </tr>\n  </tbody>\n</table>\n",
            "text/plain": "<pandas.io.formats.style.Styler at 0x1d95a65ba30>"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "execution_count": 14,
          "data": {
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Adj Close</th>\n      <th>Volume</th>\n      <th>Label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>51.630001</td>\n      <td>51.880001</td>\n      <td>51.200001</td>\n      <td>51.430000</td>\n      <td>51.430000</td>\n      <td>40772200</td>\n      <td>84.707932</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>48.799999</td>\n      <td>49.389999</td>\n      <td>47.630001</td>\n      <td>49.320000</td>\n      <td>49.320000</td>\n      <td>48670600</td>\n      <td>84.185089</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>53.430000</td>\n      <td>55.029999</td>\n      <td>53.340000</td>\n      <td>54.529999</td>\n      <td>54.529999</td>\n      <td>51640000</td>\n      <td>83.988525</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>55.189999</td>\n      <td>55.400002</td>\n      <td>54.560001</td>\n      <td>55.310001</td>\n      <td>55.310001</td>\n      <td>52365400</td>\n      <td>83.940506</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>42.200001</td>\n      <td>43.910000</td>\n      <td>39.599998</td>\n      <td>43.900002</td>\n      <td>43.900002</td>\n      <td>86689700</td>\n      <td>81.668365</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>40.189999</td>\n      <td>42.880001</td>\n      <td>38.299999</td>\n      <td>41.880001</td>\n      <td>41.880001</td>\n      <td>92741900</td>\n      <td>81.267738</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>44.299999</td>\n      <td>47.580002</td>\n      <td>44.060001</td>\n      <td>47.520000</td>\n      <td>47.520000</td>\n      <td>82294000</td>\n      <td>81.959351</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>52.240002</td>\n      <td>55.139999</td>\n      <td>52.110001</td>\n      <td>54.930000</td>\n      <td>54.930000</td>\n      <td>85306800</td>\n      <td>81.759911</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>51.070000</td>\n      <td>51.950001</td>\n      <td>49.090000</td>\n      <td>49.880001</td>\n      <td>49.880001</td>\n      <td>69562700</td>\n      <td>82.802109</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>53.430000</td>\n      <td>53.509998</td>\n      <td>51.290001</td>\n      <td>52.189999</td>\n      <td>52.189999</td>\n      <td>56560500</td>\n      <td>83.662804</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>52.900002</td>\n      <td>55.889999</td>\n      <td>52.750000</td>\n      <td>55.740002</td>\n      <td>55.740002</td>\n      <td>68746400</td>\n      <td>82.856148</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>52.099998</td>\n      <td>54.540001</td>\n      <td>51.610001</td>\n      <td>54.509998</td>\n      <td>54.509998</td>\n      <td>73814000</td>\n      <td>82.520691</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>53.029999</td>\n      <td>53.189999</td>\n      <td>52.049999</td>\n      <td>52.340000</td>\n      <td>52.340000</td>\n      <td>29081400</td>\n      <td>85.481812</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>57.540001</td>\n      <td>58.150002</td>\n      <td>55.509998</td>\n      <td>55.880001</td>\n      <td>55.880001</td>\n      <td>59839700</td>\n      <td>83.445732</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>55.310001</td>\n      <td>55.810001</td>\n      <td>54.680000</td>\n      <td>55.040001</td>\n      <td>55.040001</td>\n      <td>34710400</td>\n      <td>85.109200</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>78.430000</td>\n      <td>82.879997</td>\n      <td>77.550003</td>\n      <td>82.610001</td>\n      <td>82.610001</td>\n      <td>88513700</td>\n      <td>81.547630</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>84.300003</td>\n      <td>86.040001</td>\n      <td>84.190002</td>\n      <td>85.550003</td>\n      <td>85.550003</td>\n      <td>40723300</td>\n      <td>84.711166</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>77.660004</td>\n      <td>80.330002</td>\n      <td>75.970001</td>\n      <td>78.930000</td>\n      <td>78.930000</td>\n      <td>57874400</td>\n      <td>83.575829</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>83.059998</td>\n      <td>85.250000</td>\n      <td>82.860001</td>\n      <td>84.860001</td>\n      <td>84.860001</td>\n      <td>52177100</td>\n      <td>83.952972</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>84.739998</td>\n      <td>85.750000</td>\n      <td>82.349998</td>\n      <td>83.099998</td>\n      <td>83.099998</td>\n      <td>80354400</td>\n      <td>82.087738</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>80.930000</td>\n      <td>81.989998</td>\n      <td>79.330002</td>\n      <td>81.959999</td>\n      <td>81.959999</td>\n      <td>46557700</td>\n      <td>84.324951</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>84.239998</td>\n      <td>87.050003</td>\n      <td>82.769997</td>\n      <td>83.120003</td>\n      <td>83.120003</td>\n      <td>58580700</td>\n      <td>83.529076</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>82.730003</td>\n      <td>83.110001</td>\n      <td>80.699997</td>\n      <td>81.430000</td>\n      <td>81.430000</td>\n      <td>30423200</td>\n      <td>85.392990</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>85.760002</td>\n      <td>87.839996</td>\n      <td>85.519997</td>\n      <td>86.709999</td>\n      <td>86.709999</td>\n      <td>41349700</td>\n      <td>84.669701</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>94.050003</td>\n      <td>94.739998</td>\n      <td>91.900002</td>\n      <td>92.919998</td>\n      <td>92.919998</td>\n      <td>33907500</td>\n      <td>85.162346</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>89.550003</td>\n      <td>92.089996</td>\n      <td>89.029999</td>\n      <td>91.660004</td>\n      <td>91.660004</td>\n      <td>33804400</td>\n      <td>85.169174</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>93.360001</td>\n      <td>93.550003</td>\n      <td>90.529999</td>\n      <td>93.160004</td>\n      <td>93.160004</td>\n      <td>35673700</td>\n      <td>85.045433</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>91.800003</td>\n      <td>92.510002</td>\n      <td>91.309998</td>\n      <td>91.809998</td>\n      <td>91.809998</td>\n      <td>16705900</td>\n      <td>86.301025</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>97.860001</td>\n      <td>98.970001</td>\n      <td>94.070000</td>\n      <td>95.360001</td>\n      <td>95.360001</td>\n      <td>67672300</td>\n      <td>82.927246</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>88.309998</td>\n      <td>91.989998</td>\n      <td>87.980003</td>\n      <td>91.470001</td>\n      <td>91.470001</td>\n      <td>47639900</td>\n      <td>84.253311</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>88.150002</td>\n      <td>88.300003</td>\n      <td>85.209999</td>\n      <td>85.370003</td>\n      <td>85.370003</td>\n      <td>36930200</td>\n      <td>84.962257</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>78.029999</td>\n      <td>79.000000</td>\n      <td>73.860001</td>\n      <td>73.959999</td>\n      <td>73.959999</td>\n      <td>54563900</td>\n      <td>83.794975</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>78.489998</td>\n      <td>79.339996</td>\n      <td>77.589996</td>\n      <td>79.059998</td>\n      <td>79.059998</td>\n      <td>42283400</td>\n      <td>84.607895</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>77.550003</td>\n      <td>78.800003</td>\n      <td>76.400002</td>\n      <td>76.480003</td>\n      <td>76.480003</td>\n      <td>43753600</td>\n      <td>84.510574</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>80.160004</td>\n      <td>81.309998</td>\n      <td>79.480003</td>\n      <td>81.089996</td>\n      <td>81.089996</td>\n      <td>40182400</td>\n      <td>84.746971</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>82.800003</td>\n      <td>83.589996</td>\n      <td>82.160004</td>\n      <td>82.760002</td>\n      <td>82.760002</td>\n      <td>32759900</td>\n      <td>85.238312</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>80.919998</td>\n      <td>82.190002</td>\n      <td>80.809998</td>\n      <td>81.580002</td>\n      <td>81.580002</td>\n      <td>26387800</td>\n      <td>85.660118</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>81.870003</td>\n      <td>82.650002</td>\n      <td>80.449997</td>\n      <td>80.889999</td>\n      <td>80.889999</td>\n      <td>26956600</td>\n      <td>85.622467</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>81.610001</td>\n      <td>82.330002</td>\n      <td>80.699997</td>\n      <td>81.309998</td>\n      <td>81.309998</td>\n      <td>24310900</td>\n      <td>85.797600</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>82.900002</td>\n      <td>84.040001</td>\n      <td>82.480003</td>\n      <td>83.580002</td>\n      <td>83.580002</td>\n      <td>32107700</td>\n      <td>85.281487</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>94.040001</td>\n      <td>94.180000</td>\n      <td>91.699997</td>\n      <td>93.309998</td>\n      <td>93.309998</td>\n      <td>58059000</td>\n      <td>83.563606</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>90.760002</td>\n      <td>91.400002</td>\n      <td>88.940002</td>\n      <td>89.050003</td>\n      <td>89.050003</td>\n      <td>28108500</td>\n      <td>85.546219</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>92.010002</td>\n      <td>92.750000</td>\n      <td>91.120003</td>\n      <td>91.820000</td>\n      <td>91.820000</td>\n      <td>27668500</td>\n      <td>85.575340</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>106.639999</td>\n      <td>108.699997</td>\n      <td>105.349998</td>\n      <td>107.559998</td>\n      <td>107.559998</td>\n      <td>74053900</td>\n      <td>82.504807</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>112.610001</td>\n      <td>114.489998</td>\n      <td>111.260002</td>\n      <td>111.320000</td>\n      <td>111.320000</td>\n      <td>56130500</td>\n      <td>83.691269</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>106.279999</td>\n      <td>109.879997</td>\n      <td>106.250000</td>\n      <td>109.160004</td>\n      <td>109.160004</td>\n      <td>55631900</td>\n      <td>83.724274</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>120.830002</td>\n      <td>121.559998</td>\n      <td>118.370003</td>\n      <td>119.820000</td>\n      <td>119.820000</td>\n      <td>38992700</td>\n      <td>84.825722</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>146.029999</td>\n      <td>148.589996</td>\n      <td>144.250000</td>\n      <td>147.889999</td>\n      <td>147.889999</td>\n      <td>52162100</td>\n      <td>83.953964</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>148.000000</td>\n      <td>148.979996</td>\n      <td>142.860001</td>\n      <td>146.490005</td>\n      <td>146.490005</td>\n      <td>52271300</td>\n      <td>83.946732</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>155.759995</td>\n      <td>156.919998</td>\n      <td>153.449997</td>\n      <td>155.410004</td>\n      <td>155.410004</td>\n      <td>41668900</td>\n      <td>84.648575</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>138.190002</td>\n      <td>144.500000</td>\n      <td>135.149994</td>\n      <td>144.250000</td>\n      <td>144.250000</td>\n      <td>57785200</td>\n      <td>83.581734</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "          Open        High         Low       Close   Adj Close    Volume  \\\n0    51.630001   51.880001   51.200001   51.430000   51.430000  40772200   \n1    48.799999   49.389999   47.630001   49.320000   49.320000  48670600   \n2    53.430000   55.029999   53.340000   54.529999   54.529999  51640000   \n3    55.189999   55.400002   54.560001   55.310001   55.310001  52365400   \n4    42.200001   43.910000   39.599998   43.900002   43.900002  86689700   \n5    40.189999   42.880001   38.299999   41.880001   41.880001  92741900   \n6    44.299999   47.580002   44.060001   47.520000   47.520000  82294000   \n7    52.240002   55.139999   52.110001   54.930000   54.930000  85306800   \n8    51.070000   51.950001   49.090000   49.880001   49.880001  69562700   \n9    53.430000   53.509998   51.290001   52.189999   52.189999  56560500   \n10   52.900002   55.889999   52.750000   55.740002   55.740002  68746400   \n11   52.099998   54.540001   51.610001   54.509998   54.509998  73814000   \n12   53.029999   53.189999   52.049999   52.340000   52.340000  29081400   \n13   57.540001   58.150002   55.509998   55.880001   55.880001  59839700   \n14   55.310001   55.810001   54.680000   55.040001   55.040001  34710400   \n15   78.430000   82.879997   77.550003   82.610001   82.610001  88513700   \n16   84.300003   86.040001   84.190002   85.550003   85.550003  40723300   \n17   77.660004   80.330002   75.970001   78.930000   78.930000  57874400   \n18   83.059998   85.250000   82.860001   84.860001   84.860001  52177100   \n19   84.739998   85.750000   82.349998   83.099998   83.099998  80354400   \n20   80.930000   81.989998   79.330002   81.959999   81.959999  46557700   \n21   84.239998   87.050003   82.769997   83.120003   83.120003  58580700   \n22   82.730003   83.110001   80.699997   81.430000   81.430000  30423200   \n23   85.760002   87.839996   85.519997   86.709999   86.709999  41349700   \n24   94.050003   94.739998   91.900002   92.919998   92.919998  33907500   \n25   89.550003   92.089996   89.029999   91.660004   91.660004  33804400   \n26   93.360001   93.550003   90.529999   93.160004   93.160004  35673700   \n27   91.800003   92.510002   91.309998   91.809998   91.809998  16705900   \n28   97.860001   98.970001   94.070000   95.360001   95.360001  67672300   \n29   88.309998   91.989998   87.980003   91.470001   91.470001  47639900   \n30   88.150002   88.300003   85.209999   85.370003   85.370003  36930200   \n31   78.029999   79.000000   73.860001   73.959999   73.959999  54563900   \n32   78.489998   79.339996   77.589996   79.059998   79.059998  42283400   \n33   77.550003   78.800003   76.400002   76.480003   76.480003  43753600   \n34   80.160004   81.309998   79.480003   81.089996   81.089996  40182400   \n35   82.800003   83.589996   82.160004   82.760002   82.760002  32759900   \n36   80.919998   82.190002   80.809998   81.580002   81.580002  26387800   \n37   81.870003   82.650002   80.449997   80.889999   80.889999  26956600   \n38   81.610001   82.330002   80.699997   81.309998   81.309998  24310900   \n39   82.900002   84.040001   82.480003   83.580002   83.580002  32107700   \n40   94.040001   94.180000   91.699997   93.309998   93.309998  58059000   \n41   90.760002   91.400002   88.940002   89.050003   89.050003  28108500   \n42   92.010002   92.750000   91.120003   91.820000   91.820000  27668500   \n43  106.639999  108.699997  105.349998  107.559998  107.559998  74053900   \n44  112.610001  114.489998  111.260002  111.320000  111.320000  56130500   \n45  106.279999  109.879997  106.250000  109.160004  109.160004  55631900   \n46  120.830002  121.559998  118.370003  119.820000  119.820000  38992700   \n47  146.029999  148.589996  144.250000  147.889999  147.889999  52162100   \n48  148.000000  148.979996  142.860001  146.490005  146.490005  52271300   \n49  155.759995  156.919998  153.449997  155.410004  155.410004  41668900   \n50  138.190002  144.500000  135.149994  144.250000  144.250000  57785200   \n\n        Label  \n0   84.707932  \n1   84.185089  \n2   83.988525  \n3   83.940506  \n4   81.668365  \n5   81.267738  \n6   81.959351  \n7   81.759911  \n8   82.802109  \n9   83.662804  \n10  82.856148  \n11  82.520691  \n12  85.481812  \n13  83.445732  \n14  85.109200  \n15  81.547630  \n16  84.711166  \n17  83.575829  \n18  83.952972  \n19  82.087738  \n20  84.324951  \n21  83.529076  \n22  85.392990  \n23  84.669701  \n24  85.162346  \n25  85.169174  \n26  85.045433  \n27  86.301025  \n28  82.927246  \n29  84.253311  \n30  84.962257  \n31  83.794975  \n32  84.607895  \n33  84.510574  \n34  84.746971  \n35  85.238312  \n36  85.660118  \n37  85.622467  \n38  85.797600  \n39  85.281487  \n40  83.563606  \n41  85.546219  \n42  85.575340  \n43  82.504807  \n44  83.691269  \n45  83.724274  \n46  84.825722  \n47  83.953964  \n48  83.946732  \n49  84.648575  \n50  83.581734  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 14,
      "metadata": {},
      "id": "555a8e48"
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
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